class_docstr: Implementation of a lemmatizer based on a
  dictionary of lemmas and forms, backing off to regex rules.
  Since a given form may map to multiple lemmas,
  a corpus-based frequency disambiguator is employed.
  
  Subclasses must provide methods to load dictionary and corpora,
  and to specify regular expressions.
class_docstr_tok: ["Implementation","of","a","lemmatizer","based","on","a","dictionary","of","lemmas","and","forms",",","backing","off","to","regex","rules",".","Since","a","given","form","may","map","to","multiple","lemmas",",","a","corpus-based","frequency","disambiguator","is","employed",".","Subclasses","must","provide","methods","to","load","dictionary","and","corpora",",","and","to","specify","regular","expressions","."]
code: def __init__(self):
      self.inverted_index = self._load_forms_and_lemmas()
      self.unigram_counts = self._load_unigram_counts()
  
      self.regex_rules = [
          _build_match_and_apply_functions(pattern, replace)
          for (pattern, replace) in self._specify_regex_rules()
      ]
  
      super().__init__()
  
file_path: cltk/src/cltk/lemmatize/naive_lemmatizer.py
imports: import math
  import os
  import re
  from abc import ABC, abstractmethod
  from typing import List, Tuple, Union
  from numpy import argmax
  from cltk.utils import CLTK_DATA_DIR
label_desc: Use image node_id 1 to create a new DictionaryRegexLemmatizer object from inherited base classes: ABC with example: obj = DictionaryRegexLemmatizer()